exhaustive VS cats-effect

This is an analyzer that will catch this: https://github.com/nishanths/exhaustive

I believe it's in golangci-lint.

I agree linters in general are quite useful for Go though. The default suite from golangci-lint is quite good. I would also recommend enabling exhaustive if you're working with a codebase that uses "enums" (full disclosure, I contributed a bit to that project).

there’s a linter for exhaustive matching: https://github.com/nishanths/exhaustive

I tried to find that linter and found this: exhaustive

And in Go you'd use a linter, like this one.

this is AST go vet analyzer that performs just that: https://github.com/nishanths/exhaustive (too bad it can not do struct based enums..)

>> the main thing missing from Go is ADT's. After using these in Rust and Swift, a programming language doesn't really feel complete without them

What are the differences between an ADT (plus pattern matching i’d reckon?) in Rust/Swift vs the equiv in Go (tagged interfaces + switch statement)?

One has exhaustive matching at compile time, the other has a default clause (non exhaustive matching), although there’s an important nub here with respect to developer experience; it would be idiomatic in Go to use static analysis tooling (e.g. Rob Pike is on record saying that various checks - inc this one - don’t belong in the compiler and should live in go vet). I’ve been playing with Go in a side project and using golint-ci which invokes https://github.com/nishanths/exhaustive - net result, in both go and rust, i get a red line of text annotated at the switch in vscode if i miss a case.

Taking a step back, there isn’t a problem you can solve with one that you can’t solve with the other, or is there?

To take a step further back, why incomplete?

Use a linter.

For an exhaustive linter, were you referring to this? It looks pretty nice. If it's possible to check this with static analysis, is it something that could be in the compiler itself in the future?

https://github.com/nishanths/exhaustive

here, have fun. You’re gonna write some tests, make new types to satisfy interfaces for testing, and then wind up with branches for your test paths in your live code, but go for it, I guess. You know everything! I am but a simple blubbite, too dim, too dim to get it.

Those benchmarks are using a snapshot version of cats-effect. I don't know where that one comes from, but previously they were using a snapshot from https://github.com/typelevel/cats-effect/pull/3332 which had some issues (3.5-6581dc4, 70% performance degradation), which have since been resolved (see that PR for more info and comparative benchmarks).

Recently, CE3 has had similar issues reported across multiple repositories, almost an epidemic of reports!

The one advantage Rust has over Scala is that it detects data races at compile time, and that's a big time saver if you use low level thread synchronization. However, if you write pure FP code with ZIO or Cats Effect that's basically a non-issue anyway.

See also cats-effect and fs2. cats-effect gives you your IO Monad (and IOApp to run it with on supported platforms). fs2 is the ecosystem’s streaming library, which is much more pervasive in functional Scala than in Haskell. For example, http4s and Doobie are both based on fs2.

On the contrary, switching to the functional mindset, with something like Typelevel Scala3 and respective cats and cats-effect fs2 frameworks, helps to rethink a lot of designs and development approaches.

I think "better Haskell on JVM" (in contrast to "worse Haskell") is a good identity for Scala to have. (Please note that this is an intentional hyperbole.)

Of course, there are areas where Haskell is stronger than Scala (hint: modularity, crucial for good Software Engineering, is not one of them). And Scala has its own way of doing things, so just imitating Haskell won't work well.

Examples of this "better Haskell" are https://typelevel.org/cats-effect/ and https://zio.dev/ .

All together, Scala may be a better choice for you if you want to do Pure Functional Programming. And is definitely less risky (runs on JVM, Java libraries interop, IntelliJ, easy debugging, etc...).

None of the other languages you mentioned are viable in this sense (if also you want a powerful type system, which rules out Clojure).

I agree that Rust's identity is pretty clear: a modern language for use cases where only C or C++ could have been used before.

I would use Scala. I like FP and Scala comes with some awesome libraries for concurrent/async programming like Cats Effect or ZIO. Good choice for creating modern style micro-services to be run in the cloud (or even macro-services, Scala has a powerful module system, so it's made to handle large codebases).

https://typelevel.org/cats-effect/

https://zio.dev/

The language, the community and customs are great. You don't have to worry about nulls, things are immutable by default, domain modelling with ADTs and patter matching is pure joy.

The tooling available is from good to great and Scala is big enough that there are good libraries for typical if not vast majority of stuff and Java libs as a reliable fallback.

What took my interest is this (for both JVM and future multithreaded Scala native): https://github.com/typelevel/cats-effect/discussions/3070 Having the same threads poll available IO events and execute callbacks should improve performance greatly

The author is the creator of Monix and implemented the first version of cats-effect. He knows what he is doing.

You want Kernmantle, which quite honestly shouldn't be hard to implement around Cats and cats-effect. In particular, although Kernmantle doesn't require the use of the Arrow typeclass, there happen to be Arrow (actually ArrowChoice) instances for both Function1 from the standard library and Kleisli from Cats itself, given a Monad instance for the Kleilsi's F[_] type parameter. In other words, we should be able to port Kernmantle from Haskell to Scala (with the Typelevel ecosystem) and instantly be able to use pretty much anything else from the Typelevel ecosystem, or wrapped with it, in our workflow graphs. Pure functions, monadic functions, applicative functions, GADTs with hand-written interpreters, any of it. I think this would be eminently worth doing.